Caloriemeter: Food Calorie Estimation using Machine Learning
Pramod B. Deshmukh, Vishakha A. Metre, Rahul Pawar
Abstract
Machine Learning (ML) is a very powerful and important technology in the world today. With the help of ML modules, various appropriate algorithms such as Faster RCNN algorithm, canny edge detection algorithm and GrabCut segmentation algorithm are applied to the proposed system. This system focuses mainly on the calculation of calories and other nutrients present in food. The whole thing will be automated as opposed to existing systems where the user needs to manually deliver the values. However, users will only need to click on the food image and provide it as an input to the system. Further processes can be automated quickly, such as the use of nearer R-CNN to perceive for each food and standardization item. The GrabCut algorithm is used to get the outline of each food. Then the volume of individually food is determined by formulas for volume valuation. Lastly, it estimates the calories of each food and experimental studies have shown that by providing production with information of calories and nutrients present in the food, the proposed estimation method is effective.